Targeted Inference

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Documentation for package ‘targeted’ version 0.6

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Code demos. Use demo() to run them.
• Package NEWS.

Help Pages

aipw	AIPW estimator
alean	Assumption Lean inference for generalized linear model parameters
ate	AIPW (doubly-robust) estimator for Average Treatment Effect
ate.targeted	targeted class object
calibrate	Calibration (training)
calibration	Calibration (training)
calibration-class	calibration class object
cate	Conditional Average Treatment Effect estimation
cate_link	Conditional Relative Risk estimation
constructor_shared	Construct a learner
cross_validated	cross_validated class object
cross_validated-class	cross_validated class object
crr	Conditional Relative Risk estimation
cumhaz	Predict the cumulative hazard/survival function for a survival model
cv	Cross-validation
cv.default	Cross-validation
cv.learner_sl	Cross-validation for learner_sl
deprecated_argument_names	Deprecated argument names
deprecate_arg_warn	Cast warning for deprecated function argument names
design	Extract design matrix
estimate_truncatedscore	Estimation of mean clinical outcome truncated by event process
expand.list	Create a list from all combination of input variables
int_surv	Integral approximation of a time dependent function. Computes an approximation of \int_start^stop S(t) dt, where S(t) is a survival function, for a selection of start and stop time points.
isoreg	Pooled Adjacent Violators Algorithm
isoregw	Pooled Adjacent Violators Algorithm
learner	R6 class for prediction models
learner_expand_grid	Construct learners from a grid of parameters
learner_gam	Construct a learner
learner_glm	Construct a learner
learner_glmnet_cv	Construct a learner
learner_grf	Construct a learner
learner_hal	Construct a learner
learner_isoreg	Construct a learner
learner_mars	Construct a learner
learner_naivebayes	Construct a learner
learner_sl	Construct a learner
learner_stratify	Construct stratified learner
learner_svm	Construct a learner
learner_xgboost	Construct a learner
ML	ML model
ml_model	R6 class for prediction models
naivebayes	Naive Bayes classifier
naivebayes-class	naivebayes class object
NB	Naive Bayes classifier
nondom	Find non-dominated points of a set
pava	Pooled Adjacent Violators Algorithm
predict.density	Prediction for kernel density estimates
predict.naivebayes	Predictions for Naive Bayes Classifier
predict.superlearner	Predict Method for superlearner Fits
RATE	Responder Average Treatment Effect
RATE.surv	Responder Average Treatment Effect
riskreg	Risk regression
riskreg.targeted	targeted class object
riskreg_cens	Binary regression models with right censored outcomes
riskreg_fit	Risk regression
riskreg_mle	Risk regression
score.superlearner	Extract average cross-validated score of individual learners
scoring	Predictive model scoring
SL	SuperLearner wrapper for learner
softmax	Softmax transformation
solve_ode	Solve ODE
specify_ode	Specify Ordinary Differential Equation (ODE)
stratify	Identify Stratification Variables
superlearner	Superlearner (stacked/ensemble learner)
targeted-class	targeted class object
terms.design	Extract model component from design object
test_intersection_sw	Signed Wald intersection test
truncatedscore	Scores truncated by death
weights.superlearner	Extract ensemble weights